Lectures
All lectures will be held on Mondays at 16:15 Liivi 122
- 06.02: Association rules and decision trees by Sven Laur
- 13.02: Linear models and polynomial interpolation by Sven Laur
- 20.02: Performance evaluation measures by Sven Laur
- 27.02: Linear classification by Sven Laur
- 06.03: Introduction to optimization by Ilya Kuzovkin
- 13.03: Neural networks by Sven Laur
- 20.03: Basics of probabilistic modelling by Sven Laur
- 27.03: Maximum likelihood and maximum a posteriori estimates by Sven Laur
- 03.04: Principal Component Analysis by Sven Laur
- 10.04: Model-based clustering by Sven Laur
- 17.04: Expectation-maximisation algorithm by Sven Laur
- 24.04: Support Vector Machines by Sven Laur
- 08.05: Kernel Methods by Sven Laur
- 15.05: Elements of Statistical Learning Theory by Sven Laur
- 22.05: Ensemble Methods by Meelis Kull